Plasma p-tau217 in Alzheimer's disease: Lumipulse and ALZpath SIMOA head-to-head comparison.

Background: Plasma phosphorylated-tau217 (p-tau217) has been shown to be one of the most accurate diagnostic markers for Alzheimer's disease (AD). No studies have compared the clinical performance of p-tau217 as assessed by the fully automated Lumipulse and SIMOA ALZpath p-tau217. Aim: To evaluate the diagnostic accuracy of Lumipulse and SIMOA plasma p-tau217 assays for AD. Methods: The study included 392 participants, 162 with AD, 70 with other neurodegenerative diseases (NDD) with CSF biomarkers and 160 healthy controls. Plasma p-tau217 levels were measured using the Lumipulse and ALZpath SIMOA assays. The ability of p-tau217 assessed by both techniques to discriminate AD from NDD and controls was investigated using ROC analyses. Results: Both techniques showed high internal consistency of p-tau217 with similar correlation with CSF p-tau181 levels. In head-to-head comparison, Lumipulse and SIMOA showed similar diagnostic accuracy for differentiating AD from NDD (area under the curve [AUC] 0.952, 95%CI 0.927-0.978 vs 0.955, 95%CI 0.928-0.982, respectively) and HC (AUC 0.938, 95%CI 0.910-0.966 and 0.937, 95% CI0.907-0.967 for both assays). Conclusions: This study demonstrated the high precision and diagnostic accuracy of p-tau217 for the clinical diagnosis of Alzheimer's disease using either fully automated or semi-automated techniques.

Plasma brain-derived tau is an amyloid-associated neurodegeneration biomarker in Alzheimer's disease.

Staging amyloid-beta (Aß) pathophysiology according to the intensity of neurodegeneration could identify individuals at risk for cognitive decline in Alzheimer's disease (AD). In blood, phosphorylated tau (p-tau) associates with Aß pathophysiology but an AD-type neurodegeneration biomarker has been lacking. In this multicenter study (n = 1076), we show that brain-derived tau (BD-tau) in blood increases according to concomitant Aß ("A") and neurodegeneration ("N") abnormalities (determined using cerebrospinal fluid biomarkers); We used blood-based A/N biomarkers to profile the participants in this study; individuals with blood-based p-tau+/BD-tau+ profiles had the fastest cognitive decline and atrophy rates, irrespective of the baseline cognitive status. Furthermore, BD-tau showed no or much weaker correlations with age, renal function, other comorbidities/risk factors and self-identified race/ethnicity, compared with other blood biomarkers. Here we show that blood-based BD-tau is a biomarker for identifying Aß-positive individuals at risk of short-term cognitive decline and atrophy, with implications for clinical trials and implementation of anti-Aß therapies.

A blood-based multi-pathway biomarker assay for early detection and staging of Alzheimer's disease across ethnic groups.

INTRODUCTION: Existing blood-based biomarkers for Alzheimer's disease (AD) mainly focus on its pathological features. However, studies on blood-based biomarkers associated with other biological processes for a comprehensive evaluation of AD status are limited. METHODS: We developed a blood-based, multiplex biomarker assay for AD that measures the levels of 21 proteins involved in multiple biological pathways. We evaluated the assay's performance for classifying AD and indicating AD-related endophenotypes in three independent cohorts from Chinese or European-descent populations. RESULTS: The 21-protein assay accurately classified AD (area under the receiver operating characteristic curve [AUC] = 0.9407 to 0.9867) and mild cognitive impairment (MCI; AUC = 0.8434 to 0.8945) while also indicating brain amyloid pathology. Moreover, the assay simultaneously evaluated the changes of five biological processes in individuals and revealed the ethnic-specific dysregulations of biological processes upon AD progression. DISCUSSION: This study demonstrated the utility of a blood-based, multi-pathway biomarker assay for early screening and staging of AD, providing insights for patient stratification and precision medicine. HIGHLIGHTS: The authors developed a blood-based biomarker assay for Alzheimer's disease. The 21-protein assay classifies AD/MCI and indicates brain amyloid pathology. The 21-protein assay can simultaneously assess activities of five biological processes. Ethnic-specific dysregulations of biological processes in AD were revealed.

A novel ultrasensitive assay for plasma p-tau217: Performance in individuals with subjective cognitive decline and early Alzheimer's disease.

INTRODUCTION: Detection of Alzheimer's disease (AD) pathophysiology among individuals with mild cognitive changes and those experiencing subjective cognitive decline (SCD) remains challenging. Plasma phosphorylated tau 217 (p-tau217) is one of the most promising of the emerging biomarkers for AD. However, accessible methods are limited. METHODS: We employed a novel p-tau217 immunoassay (University of Gothenburg [UGOT] p-tau217) in four independent cohorts (n = 308) including a cerebrospinal fluid (CSF) biomarker-classified cohort (Discovery), two cohorts consisting mostly of cognitively unimpaired (CU) and mild cognitively impaired (MCI) participants (MYHAT and Pittsburgh), and a population-based cohort of individuals with SCD (Barcelonaßeta Brain Research Center's Alzheimer's At-Risk Cohort [ß-AARC]). RESULTS: UGOT p-tau217 showed high accuracy (area under the curve [AUC] = 0.80-0.91) identifying amyloid beta (Aß) pathology, determined either by Aß positron emission tomography or CSF Aß42/40 ratio. In individuals experiencing SCD, UGOT p-tau217 showed high accuracy identifying those with a positive CSF Aß42/40 ratio (AUC = 0.91). DISCUSSION: UGOT p-tau217 can be an easily accessible and efficient way to screen and monitor patients with suspected AD pathophysiology, even in the early stages of the continuum.

Risk of cognitive decline progression is associated to increased blood-brain-barrier permeability: A longitudinal study in a memory unit clinical cohort.

INTRODUCTION: This study examined the relationship between blood-brain-barrier permeability (BBBp), measured by cerebrospinal fluid/serum albumin ratio (QAlb), and cognitive decline progression in a clinical cohort. METHODS: This prospective observational study included 334 participants from the BIODEGMAR cohort. Cognitive decline progression was defined as an increase in Global Deterioration Scale and/or Clinical Dementia Rating scores. Associations between BBBp, demographics, and clinical factors were explored. RESULTS: Male sex, diabetes mellitus, and cerebrovascular burden were associated with increased log-QAlb. Vascular cognitive impairment patients had the highest log-QAlb levels. Among the 273 participants with valid follow-up data, 154 (56.4%) showed cognitive decline progression. An 8% increase in the hazard of clinical worsening was observed for each 10% increase in log-QAlb. DISCUSSION: These results suggest that increased BBBp in individuals with cognitive decline may contribute to clinical worsening, pointing to potential targeted therapies. QAlb could be a useful biomarker for identifying patients with a worse prognosis.

A novel ultrasensitive assay for plasma p-tau217: performance in individuals with subjective cognitive decline and early Alzheimer's disease.

INTRODUCTION: Detection of Alzheimer's disease (AD) pathophysiology among cognitively unimpaired individuals and those experiencing subjective cognitive decline (SCD) remains challenging. Plasma p-tau217 is one of the most promising of the emerging biomarkers for AD. However, accessible methods are limited. METHODS: We employed a novel p-tau217 immunoassay (UGOT p-tau217) in four independent cohorts (n=308) including a cerebrospinal fluid (CSF) biomarker-classified cohort (Discovery), two cohorts consisting mostly of cognitively unimpaired participants (MYHAT and Pittsburgh), and a population-based cohort of individuals with SCD (ß-AARC). RESULTS: UGOT p-tau217 showed high accuracy (AUC= 0.80-0.91) identifying Aß pathology, determined either by Aß positron emission tomography or CSF Aß42/40 ratio. In individuals experiencing SCD, UGOT p-tau217 showed high accuracy identifying those with a positive CSF Aß42/40 ratio (AUC= 0.91). DISCUSSION: UGOT p-tau217 can be an easily accessible and efficient way to screen and monitor patients with suspected AD pathophysiology, even in the early stages of the continuum.

Agreement of cerebrospinal fluid biomarkers and amyloid-PET in a multicenter study.

Core Alzheimer's disease (AD) cerebrospinal fluid (CSF) biomarkers have shown incomplete agreement with amyloid-positron emission tomography (PET). Our goal was to analyze the agreement between AD CSF biomarkers and amyloid-PET in a multicenter study. Retrospective multicenter study (5 centers). Participants who underwent both CSF biomarkers and amyloid-PET scan within 18 months were included. Clinical diagnoses were made according to latest diagnostic criteria by the attending clinicians. CSF Amyloid Beta1-42 (Aß1-42, A), phosphorliated tau 181 (pTau181, T) and total tau (tTau, N) biomarkers were considered normal (-) or abnormal ( +) according to cutoffs of each center. Amyloid-PET was visually classified as positive/negative. Agreement between CSF biomarkers and amyloid-PET was analyzed by overall percent agreement (OPA). 236 participants were included (mean age 67.9 years (SD 9.1), MMSE score 24.5 (SD 4.1)). Diagnoses were mild cognitive impairment or dementia due to AD (49%), Lewy body dementia (22%), frontotemporal dementia (10%) and others (19%). Mean time between tests was 5.1 months (SD 4.1). OPA between single CSF biomarkers and amyloid-PET was 74% for Aß1-42, 75% for pTau181, 73% for tTau. The use of biomarker ratios improved OPA: 87% for Aß1-42/Aß1-40 (n = 155), 88% for pTau181/Aß1-42 (n = 94) and 82% for tTau/Aß1-42 (n = 160). A + T + N + cases showed the highest agreement between CSF biomarkers and amyloid-PET (96%), followed by A-T-N- cases (89%). Aß1-42/Aß1-40 was a better marker of cerebral amyloid deposition, as identified by amyloid tracers, than Aß1-42 alone. Combined biomarkers in CSF predicted amyloid-PET result better than single biomarkers.

Thalamic nuclei changes in early and late onset Alzheimer's disease.

Alzheimer's disease (AD) is the most common cause of dementia worldwide. Increasing evidence points to the thalamus as an important hub in the clinical symptomatology of the disease, with the 'limbic thalamus' been described as especially vulnerable. In this work, we examined thalamic atrophy in early-onset AD (EOAD) and late-onset AD (LOAD) compared to young and old healthy controls (YHC and OHC, respectively) using a recently developed cutting-edge thalamic nuclei segmentation method. A deep learning variant of Thalamus Optimized Multi Atlas Segmentation (THOMAS) was used to parcellate 11 thalamic nuclei per hemisphere from T1-weighted MRI in 88 biomarker-confirmed AD patients (49 EOAD and 39 LOAD) and 58 healthy controls (41 YHC and 17 OHC) with normal AD biomarkers. Nuclei volumes were compared among groups using MANCOVA. Further, Pearson's correlation coefficient was computed between thalamic nuclear volume and cortical-subcortical regions, CSF tau levels, and neuropsychological scores. The results showed widespread thalamic nuclei atrophy in EOAD and LOAD compared to their respective healthy control groups, with EOAD showing additional atrophy in the centromedian and ventral lateral posterior nuclei compared to YHC. In EOAD, increased thalamic nuclei atrophy was associated with posterior parietal atrophy and worse visuospatial abilities, while LOAD thalamic nuclei atrophy was preferentially associated with medial temporal atrophy and worse episodic memory and executive function. Our findings suggest that thalamic nuclei may be differentially affected in AD according to the age at symptoms onset, associated with specific cortical-subcortical regions, CSF total tau and cognition.

Classifying Alzheimer's disease and frontotemporal dementia using machine learning with cross-sectional and longitudinal magnetic resonance imaging data.

Alzheimer's disease (AD) and frontotemporal dementia (FTD) are common causes of dementia with partly overlapping, symptoms and brain signatures. There is a need to establish an accurate diagnosis and to obtain markers for disease tracking. We combined unsupervised and supervised machine learning to discriminate between AD and FTD using brain magnetic resonance imaging (MRI). We included baseline 3T-T1 MRI data from 339 subjects: 99 healthy controls (CTR), 153 AD and 87 FTD patients; and 2-year follow-up data from 114 subjects. We obtained subcortical gray matter volumes and cortical thickness measures using FreeSurfer. We used dimensionality reduction to obtain a single feature that was later used in a support vector machine for classification. Discrimination patterns were obtained with the contribution of each region to the single feature. Our algorithm differentiated CTR versus AD and CTR versus FTD at the cross-sectional level with 83.3% and 82.1% of accuracy. These increased up to 90.0% and 88.0% with longitudinal data. When we studied the classification between AD versus FTD we obtained an accuracy of 63.3% at the cross-sectional level and 75.0% for longitudinal data. The AD versus FTD versus CTR classification has reached an accuracy of 60.7%, and 71.3% for cross-sectional and longitudinal data respectively. Disease discrimination brain maps are in concordance with previous results obtained with classical approaches. By using a single feature, we were capable to classify CTR, AD, and FTD with good accuracy, considering the inherent overlap between diseases. Importantly, the algorithm can be used with cross-sectional and longitudinal data.

Diagnostic Performance and Clinical Applicability of Blood-Based Biomarkers in a Prospective Memory Clinic Cohort.

BACKGROUND AND OBJECTIVES: Blood-based biomarkers have emerged as minimally invasive options for evaluating cognitive impairment. Most studies to date have assessed them in research cohorts, limiting their generalization to everyday clinical practice. We evaluated their diagnostic performance and clinical applicability in a prospective, real-world, memory clinic cohort. METHODS: All patients referred with suspected cognitive impairment between July 2019 and June 2021 were prospectively invited to participate. Five plasma biomarkers (tau phosphorylated at threonine 181 [p-tau181], glial fibrillary acidic protein [GFAP], neurofilament light chain [NfL], total tau [t-tau], and ubiquitin C-terminal hydrolase L1 [UCH-L1]) were determined with single-molecule array. Performance was assessed in comparison to clinical diagnosis (blinded to plasma results) and amyloid status (CSF/PET). A group of cognitively unimpaired (CU) controls was also included. RESULTS: Three hundred forty-nine participants (mean age 68, SD 8.3 years) and 36 CU controls (mean age 61.7, SD 8.2 years) were included. In the subcohort with available Alzheimer disease (AD) biomarkers (n = 268), plasma p-tau181 and GFAP had a high diagnostic accuracy to differentiate AD from non-neurodegenerative causes (area under the receiver operating characteristic curve 0.94 and 0.92, respectively), with p-tau181 systematically outperforming GFAP. Plasma p-tau181 levels predicted amyloid status (85% sensitivity and specificity) with accurate individual prediction in approximately 60% of the patients. Plasma NfL differentiated frontotemporal dementia (FTD) syndromes from CU (0.90) and non-neurodegenerative causes (0.93), whereas the discriminative capacity with AD and between all neurodegenerative and non-neurodegenerative causes was less accurate. A combination of p-tau181 and NfL identified FTD with 82% sensitivity and 85% specificity and had a negative predictive value for neurodegenerative diagnosis of 86%, ruling out half of the non-neurodegenerative diagnoses. In the subcohort without AD biomarkers, similar results were obtained. T-tau and UCH-L1 did not offer added diagnostic value. DISCUSSION: Plasma p-tau181 predicted amyloid status with high accuracy and could have potentially avoided CSF/amyloid PET testing in approximately 60% of subjects in a memory clinic setting. NfL was useful for identifying FTD from non-neurodegenerative causes but behaved worse than p-tau181 in all other comparisons. Combining p-tau181 and NfL improved diagnostic performance for FTD and non-neurodegenerative diagnoses. However, the 14% false-negative results suggest that further improvement is needed before implementation outside memory clinics. CLASSIFICATION OF EVIDENCE: This study provides Class I evidence that plasma p-tau181 correlates with the presence or absence of AD and a combination of plasma p-tau181 and NfL correlates moderately well with a diagnosis of FTD.

The APOE4 effect: structural brain differences in Alzheimer's disease according to the age at symptom onset.

BACKGROUND AND PURPOSE: How the APOE genotype can differentially affect cortical and subcortical memory structures in biomarker-confirmed early-onset (EOAD) and late-onset (LOAD) Alzheimer's disease (AD) was assessed. METHOD: Eighty-seven cerebrospinal fluid (CSF) biomarker-confirmed AD patients were classified according to their APOE genotype and age at onset. 28 were EOAD APOE4 carriers (+EOAD), 21 EOAD APOE4 non-carriers (-EOAD), 23 LOAD APOE4 carriers (+LOAD) and 15 LOAD APOE4 non-carriers (-LOAD). Grey matter (GM) volume differences were analyzed using voxel-based morphometry in Papez circuit regions. Multiple regression analyses were performed to determine the relation between GM volume loss and cognition. RESULTS: Significantly more mammillary body atrophy in +EOAD compared to -EOAD is reported. The medial temporal and posterior cingulate cortex showed less GM in +LOAD compared to -LOAD. Medial temporal GM volume loss was also found in +EOAD compared to -LOAD. With an exception for +EOAD, medial temporal GM was strongly associated with episodic memory in the three groups, whilst posterior cingulate cortex GM volume was more related with visuospatial abilities. Visuospatial abilities and episodic memory were also associated with the anterior thalamic nucleus in -LOAD. CONCLUSIONS: Our results show that the APOE genotype has a significant effect on GM integrity as a function of age of disease onset. Specifically, whilst LOAD APOE4 genotype is mostly associated with increased medial temporal and parietal atrophy compared to -LOAD, for EOAD APOE4 might have a more specific effect on subcortical (mammillary body) structures. The findings suggest that APOE genotype needs to be taken into account when classifying patients by age at onset.

Cost-effectiveness of Alzheimer's disease CSF biomarkers and amyloid-PET in early-onset cognitive impairment diagnosis.

This study aimed at determining the cost-effectiveness of amyloid-positron emission tomography (PET) compared to Alzheimer's disease (AD) cerebrospinal fluid (CSF) biomarkers (amyloid-ß42, total-Tau and phosphorylated-Tau) for the diagnosis of AD in patients with early-onset cognitive impairment. A decision tree model using a national health care perspective was developed to compare the costs and effectiveness associated with Amyloid-PET and AD CSF biomarkers. Available evidence from the literature and primary data from Hospital Clínic de Barcelona were used to inform the model and calculate the efficiency of these diagnostic alternatives. Medical visits and diagnostic procedures were considered and reported in €2020. We calculated the incremental cost-effectiveness ratio to measure the cost per % of correct diagnoses detected and we perform one-way deterministic and probabilistic sensitivity analyses to assess the uncertainty of these results. Compared with AD CSF biomarkers, Amyloid-PET resulted in 7.40% more correctly diagnosed cases of AD, with an incremental total mean cost of €146,854.80 per 100 cases. We found a 50% of probability that Amyloid-PET was cost-effective for a willingness to pay (WTP) of €19,840.39 per correct case detected. Using a WTP of €75,000, the probability that it is cost-effective reached a maximum of 76.9%, thus leading to a conclusion that Amyloid-PET is not a cost-effective technique compared to AD CSF biomarkers, unless the funder is willing to pay a minimum of €19,840.39 to detect one more correct case. Furthermore, obtaining CSF provides simultaneous information on amyloid ß and tau biomarkers and allows other biomarkers to be analyzed at a relatively low cost.

Early-onset Alzheimer's disease shows a distinct neuropsychological profile and more aggressive trajectories of cognitive decline than late-onset.

OBJECTIVES: Early- and late-onset Alzheimer's disease (EOAD and LOAD) share the same neuropathological traits but show distinct cognitive features. We aimed to explore baseline and longitudinal outcomes of global and domain-specific cognitive function in a well characterized cohort of patients with a biomarker-based diagnosis. METHODS: In this retrospective cohort study, 195 participants were included and classified according to their age, clinical status, and CSF AD biomarker profile: 89 EOAD, 37 LOAD, 46 young healthy controls (age ≤ 65 years), and 23 old healthy controls (>65 years). All subjects underwent clinical and neuropsychological assessment, neuroimaging, APOE genotyping and lumbar puncture. RESULTS: We found distinct neuropsychological profiles between EOAD and LOAD at the time of diagnosis. Both groups showed similar performances on memory and language domains, but the EOAD patients displayed worsened deficits in visual perception, praxis, and executive tasks (p < 0.05). Longitudinally, cognitive decline in EOAD was more pronounced than LOAD in the global outcomes at the expense of these non-amnestic domains. We found that years of education significantly influenced the decline in most of the neuropsychological tests. Besides, the APOE ε4 status showed a significant effect on the decline of memory-related tasks within the EOAD cohort (p < 0.05). INTERPRETATION: Age of onset is a main factor shaping the cognitive trajectories in AD patients, with younger age driving to a steeper decline of the non-memory domains. Years of education are related to a transversal decline in all cognitive domains and APOE ε4 status to a specific decline in memory performance in EOAD.

Sex differences in early-onset Alzheimer's disease.

BACKGROUND AND PURPOSE: Sex is believed to drive heterogeneity in Alzheimer's disease (AD), although evidence in early-onset AD (EOAD; <65 years) is scarce. METHODS: We included 62 EOAD patients and 44 healthy controls (HCs) with core AD cerebrospinal fluid (CSF) biomarkers, neurofilament light chain levels, neuropsychological assessment, and 3-T magnetic resonance imaging. We measured cortical thickness (CTh) and hippocampal subfield volumes (HpS) using FreeSurfer. Adjusted linear models were used to analyze sex-differences and the relationship between atrophy and cognition. RESULTS: Compared to same-sex HCs, female EOAD subjects showed greater cognitive impairment and broader atrophy burden than male EOAD subjects. In a direct female-EOAD versus male-EOAD comparison, there were slight differences in temporal CTh, with no differences in cognition or HpS. CSF tau levels were higher in female EOAD than in male EOAD subjects. Greater atrophy was associated with worse cognition in female EOAD subjects. CONCLUSIONS: At diagnosis, there are sex differences in the pattern of cognitive impairment, atrophy burden, and CSF tau in EOAD, suggesting there is an influence of sex on pathology spreading and susceptibility to the disease in EOAD.

Evaluating the performance of Bayesian and frequentist approaches for longitudinal modeling: application to Alzheimer's disease.

Linear mixed effects (LME) modelling under both frequentist and Bayesian frameworks can be used to study longitudinal trajectories. We studied the performance of both frameworks on different dataset configurations using hippocampal volumes from longitudinal MRI data across groups-healthy controls (HC), mild cognitive impairment (MCI) and Alzheimer's disease (AD) patients, including subjects that converted from MCI to AD. We started from a big database of 1250 subjects from the Alzheimer's disease neuroimaging initiative (ADNI), and we created different reduced datasets simulating real-life situations using a random-removal permutation-based approach. The number of subjects needed to differentiate groups and to detect conversion to AD was 147 and 115 respectively. The Bayesian approach allowed estimating the LME model even with very sparse databases, with high number of missing points, which was not possible with the frequentist approach. Our results indicate that the frequentist approach is computationally simpler, but it fails in modelling data with high number of missing values.

Evolution of Clinical-Pathological Correlations in Early-Onset Alzheimer's Disease Over a 25-Year Period in an Academic Brain Bank.

BACKGROUND: Early onset Alzheimer's disease (EOAD) represents a diagnostic challenge and is associated with a high diagnostic delay and misdiagnosis. OBJECTIVE: To describe clinical and pathological data from a pathologically confirmed EOAD cohort and evaluate evolving trends in clinical-pathological correlation accuracy. METHODS: Retrospective review of clinical and neuropathological data of pathologically confirmed EOAD patients (age at onset [AAO] < 60). Comparison between two periods: 1994- 2009 and 2010- 2018. RESULTS: Eighty brain donors were included. Mean AAO, age at death, and diagnostic delay was 55, 66, and 3 years, respectively. Twenty-nine percent had a nonamnestic presentation. Sixteen percent were given a non-AD initial clinical diagnosis (initial misdiagnosis) and 14% received a final misdiagnosis. Nonamnestic presentation patients received more misdiagnoses than amnestic presentation ones (39% versus 7% and 39% versus 3.5%, on initial and final misdiagnosis, respectively). When comparing both time periods, a trend towards a higher diagnostic accuracy in the 2010- 2018 period was observed, mainly on initial misdiagnosis in nonamnestic presentation patients (53% versus 13%, p = 0.069). Diagnostic delay was similar between both periods. Cerebral amyloid angiopathy (96%) and Lewy body co-pathology (55%) were very frequent, while limbic-predominant age-related TDP-43 encephalopathy pathologic changes were only present in 12.5%. CONCLUSION: In the last decade, there has been a trend towards improved diagnostic accuracy in EOAD, which might be explained by improved diagnostic criteria, increasing experience on EOAD and the beginning of the use of biomarkers, although diagnostic delay remains similar. Concomitant neuropathology was very frequent despite the relatively young age of brain donors.

Baseline MRI atrophy predicts 2-year cognitive outcomes in early-onset Alzheimer's disease.

BACKGROUND: MRI atrophy predicts cognitive status in AD. However, this relationship has not been investigated in early-onset AD (EOAD, < 65 years) patients with a biomarker-based diagnosis. METHODS: Forty eight EOAD (MMSE ≥ 15; A + T + N +) and forty two age-matched healthy controls (HC; A - T - N -) from a prospective cohort underwent full neuropsychological assessment, 3T-MRI scan and lumbar puncture at baseline. Participants repeated the cognitive assessment annually. We used linear mixed models to investigate whether baseline cortical thickness (CTh) or subcortical volume predicts two-year cognitive outcomes in the EOAD group. RESULTS: In EOAD, hemispheric CTh and ventricular volume at baseline were associated with global cognition, language and attentional/executive functioning 2 years later (p < 0.0028). Regional CTh was related to most cognitive outcomes (p < 0.0028), except verbal/visual memory subtests. Amygdalar volume was associated with letter fluency test (p < 0.0028). Hippocampal volume did not show significant associations. CONCLUSION: Baseline hemispheric/regional CTh, ventricular and amygdalar volume, but not the hippocampus, predict two-year cognitive outcomes in EOAD.

Longitudinal brain atrophy and CSF biomarkers in early-onset Alzheimer's disease.

There is evidence of longitudinal atrophy in posterior brain areas in early-onset Alzheimer's disease (EOAD; aged < 65 years), but no studies have been conducted in an EOAD cohort with fluid biomarkers characterization. We used 3T-MRI and Freesurfer 6.0 to investigate cortical and subcortical gray matter loss at two years in 12 EOAD patients (A + T + N + ) compared to 19 controls (A-T-N-) from the Hospital Clínic Barcelona cohort. We explored group differences in atrophy patterns and we correlated atrophy and baseline CSF-biomarkers levels in EOAD. We replicated the correlation analyses in 14 EOAD (A + T + N + ) and 55 late-onset AD (LOAD; aged ≥ 75 years; A + T + N + ) participants from the Alzheimer's disease Neuroimaging Initiative. We found that EOAD longitudinal atrophy spread with a posterior-to-anterior gradient and beyond hippocampus/amygdala. In EOAD, higher initial CSF NfL levels correlated with higher ventricular volumes at baseline. On the other hand, higher initial CSF Aß42 levels (within pathological range) predicted higher rates of cortical loss in EOAD. In EOAD and LOAD subjects, higher CSF t-tau values at baseline predicted higher rates of subcortical atrophy. CSF p-tau did not show any significant correlation. In conclusion, posterior cortices, hippocampus and amygdala capture EOAD atrophy from early stages. CSF Aß42 might predict cortical thinning and t-tau/NfL subcortical atrophy.